Digital Transformation

The three 'C's in CTV buying: contextual, consistency and clean rooms

By Peter Mason | Cofounder and chief executive officer

June 10, 2022 | 6 min read

For the CTV advertising to reach its full potential while preserving consumer data privacy, the industry needs to invest more deeply in contextual solutions and clean rooms, argues Illuma cofounder and chief executive Peter Mason.

Apple TV remote control in person's hand

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Connected television (CTV) is being held up as the big programmatic opportunity in post-pandemic digital advertising, as audiences have moved en masse towards streaming and video services over the last two years.

But it’s early days and like all digital evolutions before it, CTV is experiencing growing pains as it matures and becomes more accessible for buyers. On addition to the oft-mentioned shortage of supply-side data and inventory, as things stand, CTV ad targeting is also compartmentalized and siloed, and there are few ways to target that reflect the fluidity of audience movement between platforms.

In order for CTV to accelerate and meet its potential, both the buy and sell sides need to start viewing it within the broader omnichannel media mix. This can be achieved by smarter use of contextual signals, better consistency in the data exchange and supporting the whole process with clean rooms.

Contextual signals: connecting the dots between platforms

As technology develops and supports greater innovation, it’s becoming possible to break down some of these barriers and target across platforms. Contextual signals are key here; used carefully, page-level intelligence from a campaign’s best-performing contexts on the open web can be repurposed to make smarter live buying decisions in CTV. In turn, CTV insights can inform open web digital buys, giving a dynamic, near-real-time, actionable understanding of audience interests and the contexts that are delivering the best results.

In an ambitious yet plausible construct, this loop can eventually connect the full range of marketer channels including linear TV and even audio.

All of this is becoming possible thanks to the rich behavioral-contextual data being being surfaced by a new generation of AI-based targeting tools. And the ability to absorb and react to consumer signals in an evolving omnichannel mediascape is connecting the dots between these siloed spaces and has the potential to drive more efficient and powerful results.

Consistency between supply and demand

But in order for this integrated, omnichannel marketplace to be fully realized, the CTV supply side needs to continue to trust in the mutual benefits of open, transparent sharing of data with the demand side. By being more open about specific content consumption patterns on their platforms, all players in the ecosystem would benefit from a live, cookieless information symmetry that could act as a force multiplier for growth.

Traditional broadcasters are still coming to terms with balancing the interests of their legacy linear businesses with those in CTV, but it’s great to see them gradually starting to move in this direction. By continuing to open up their data, they too will reap the rewards that will come from more granular and connected CTV targeting.

Multi-touch attribution (MTA) may even come into reach. The industry has been grappling with MTA for years, but it has always been stymied by a lack of cohesion, providing only a disjointed view of consumer behavior. Of course, it’ll take more than supply-side data alone to make full MTA a reality, but it would certainly help inform hybrid models that could also include the traditional marketing mix modeling that is back in vogue.

In time, better collaboration will also make it possible for these new integrated data architectures to use other deterministic data and probabilistic signals. At the end of the day, collaboration and flexibility will be key to post-cookie success, and we all need to be clear-eyed about the shifting consumer patterns which are clearly trending towards CTV — and recalibrate our efforts accordingly.

Clean rooms and greater data collaboration

Emergent data clean rooms like Snowflake and InfoSum are supporting the ecosystem’s increasing focus on higher quality data by unifying disparate elements —without compromising on consumer privacy. As they develop, clean rooms will help maximize the opportunities presented by first-party data from brands and publishers and, in the process, contribute to this potential live dynamic feedback loop.

Early efforts by some broadcasters point to the potential of using clean rooms to synthesize and direct this live behavioral information from the open web and CTV. In realizing this potential, marketers would be able to optimize in a manner far superior to the shoddy lookalike modeling for which they’ve been forced to settle.

As these dynamics play out, one thing is certain: our industry has the tools to create a post-cookie paradigm built upon contextual solutions and clean rooms that can support an omnichannel approach and benefit all players. This new paradigm will be thoughtful, efficient and privacy-centric. We need only commit will and consistent resources to turn this opportunity into reality.

Peter Mason is cofounder and chief executive officer at Illuma.

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